Summary of Federated Learning Clients Clustering with Adaptation to Data Drifts, by Minghao Li (1) et al.
Federated Learning Clients Clustering with Adaptation to Data Driftsby Minghao Li, Dmitrii Avdiukhin, Rana Shahout,…
Federated Learning Clients Clustering with Adaptation to Data Driftsby Minghao Li, Dmitrii Avdiukhin, Rana Shahout,…
Can Large Language Model Predict Employee Attrition?by Xiaoye Ma, Weiheng Liu, Changyi Zhao, Liliya R.…
HOBBIT: A Mixed Precision Expert Offloading System for Fast MoE Inferenceby Peng Tang, Jiacheng Liu,…
AttackQA: Development and Adoption of a Dataset for Assisting Cybersecurity Operations using Fine-tuned and Open-Source…
Using Half-Precision for GNN Trainingby Arnab Kanti Tarafder, Yidong Gong, Pradeep KumarFirst submitted to arxiv…
Computation-Aware Gaussian Processes: Model Selection And Linear-Time Inferenceby Jonathan Wenger, Kaiwen Wu, Philipp Hennig, Jacob…
Introduction to AI Safety, Ethics, and Societyby Dan HendrycksFirst submitted to arxiv on: 1 Nov…
GWQ: Gradient-Aware Weight Quantization for Large Language Modelsby Yihua Shao, Siyu Liang, Zijian Ling, Minxi…
Physics in Next-token Predictionby Hongjun An, Yiliang Song, Xuelong LiFirst submitted to arxiv on: 1…
Outlier-Oriented Poisoning Attack: A Grey-box Approach to Disturb Decision Boundaries by Perturbing Outliers in Multiclass…